The purpose of performance profiling (experimental analysis) is to measure the program/algorithm performance. Assume that you have performed an experimental analysis of an algorithm, and profiling returned the following times: for instances of sizes 2^10, 2^11, 2^12, 2^13, 2^14
the corresponding times are approximately 300 , 510 , 905 , 1750 , 3305 milliseconds.
In these collected running times, there is an extra overhead resulting from clocking program performance and OS functions calls, and this overhead has to be considered in analyzing data. That is, the measured time consists of two components: the time for executing the operations, plus the overhead from profiling.
The estimated overhead due to profiling is about 100 milliseconds independently of the input size. (that is, 100 is always an additive ``constant'' in the collected times).
Based on these experimental results, what is the running time, as a function of the problem size, for executing this algorithm? (c is a constant).
A. O(underroot(n)).
B. O(n^2).
C. O(n).
D. None of the listed.
E. O(n log n).